Find Your Next Software Engineering Role Faster

Own the architecture and hands-on development of Mercor’s code search and retrieval systems, combining dense code embeddings, BM25, ranking, indexing, and model routing. Set technical direction across the organization while building search infrastructure for frontier coding-model evaluation and training.

Build and productionize quantized VLA and LLM inference systems for XPENG’s next-generation Turing AI chip and autonomous-driving platforms. This staff-level role combines model optimization, deployment pipelines, numerical validation, and cross-functional performance sign-off.

Develop and productionize LLM quantization and VLA inference systems for deployment on XPENG’s Turing AI chip and autonomous vehicles. The role combines model optimization, benchmarking, deployment pipelines, and cross-functional performance sign-off.

Build and deploy responsible machine learning capabilities across Axon’s public safety products, from model training and evaluation to cloud and device deployment. This Seattle hybrid role combines AI platform architecture, hands-on engineering, and collaboration with scientists and product teams.

Build the data infrastructure and active-learning systems that continuously improve Waymo’s autonomous-driving perception models. You’ll connect model architecture with large-scale sensor-data curation, evaluation, and production machine-learning pipelines.

Build production-grade software and machine learning systems for behavior prediction, decision-making, and autonomy in dynamic physical environments. You’ll work across data pipelines, model evaluation, scalable infrastructure, and low-latency deployment.

Lead DiDi Autonomous Driving’s transition to an AI-Native engineering organization by designing scalable LLM infrastructure and embedding directly with autonomous driving teams. This hands-on principal role combines systems architecture, distributed AI optimization, and forward-deployed execution across mission-critical engineering environments.

Build the data, model, and agent-runtime infrastructure behind Dexmate’s Physical AI platform. You’ll move robot data and AI models from experimentation into scalable, reliable production systems.